Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links
Paper Citation Record · LEDGER
NoisyGL: A Comprehensive Benchmark for Graph Neural Networks under Label Noise
As of 8 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 2 inbound Pith citation observations for arXiv:2406.04299.
A citation records a reference. It does not transfer a finding from one paper to another.
Coverage vector
One-hop event checks from named stored sources.
Source: scholarly_work_events, retraction_status_cache, observed 2026-08-08T06:32:00.761636+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links, observed 2026-08-07T00:55:54.842692Z
A source-named dated measurement, never combined with another source.
Source: pith, observed 2026-08-07T00:55:54.941360Z
Reference resolution
0 of 0 outbound references displayed
- verified exact0
- verified fuzzy0
- unresolved0
- parse uncertain0
- malformed identifier0
- metadata mismatch0
External citation measurements
No source-named external measurement is stored.
Outbound references
No outbound reference observations are available for this paper version.
Pith citing papers
Observation c7ee6925-deff-4bb9-ac39-ed403865d7a5 · inbound
Delving into Instance-Dependent Label Noise in Graph Data: A Comprehensive Study and Benchmark cites this paper.
Delving into Instance-Dependent Label Noise in Graph Data: A Comprehensive Study and Benchmark NoisyGL: A Comprehensive Benchmark for Graph Neural Networks under Label Noise
Reference 61
- Resolution
- verified exact
- local_arxiv, observed 2026-08-07T00:55:54.946991Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.
Observation 527bdd1a-ecd6-4d47-9d48-5422dfda2106 · inbound
OpenRTAG: A Comprehensive Benchmark for Robust Text-Attributed Graph Learning under Data Quality Degradation cites this paper.
OpenRTAG: A Comprehensive Benchmark for Robust Text-Attributed Graph Learning under Data Quality Degradation NoisyGL: A Comprehensive Benchmark for Graph Neural Networks under Label Noise
Reference 27
- Resolution
- unresolved
- no resolver link, observed 2026-08-01T13:29:53.613715Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.